The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning
Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for contro...
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| Format: | Article |
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MDPI AG
2021-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/15/5244 |
| _version_ | 1797411258597638144 |
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| author | Ryszard K. Miler Andrzej Kuriata Anna Brzozowska Akram Akoel Antonina Kalinichenko |
| author_facet | Ryszard K. Miler Andrzej Kuriata Anna Brzozowska Akram Akoel Antonina Kalinichenko |
| author_sort | Ryszard K. Miler |
| collection | DOAJ |
| description | Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for controlling algorithms. The aim of this paper is to present a game-based algorithm of controlling behaviours in the relation between an operator (OP) and a technical object (TO), based on the assumption that the game is logistics-oriented and the algorithm is to support ML applied in e-commerce optimization management. Algebraic methods, including matrices, Lagrange functions, systems of differential equations, and set-theoretic notation, have been used as the main tools. The outcome is a model of a game-based optimization process in a two-element logistics system and an algorithm applied to find optimal steering strategies. The algorithm has been initially verified with the use of simulation based on a Bayesian network (BN) and a structured set of possible strategies (OP/TO) calculated with the use of QGeNie Modeller, finally prepared for Python. It has been proved the algorithm at this stage has no deadlocks and unforeseen loops and is ready to be challenged with the original big set of learning data from a drone-operating company (as the next stage of the planned research). |
| first_indexed | 2024-03-09T04:42:29Z |
| format | Article |
| id | doaj.art-eaed5fb7bca841309fce1ce35abf2e70 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T04:42:29Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-eaed5fb7bca841309fce1ce35abf2e702023-12-03T13:19:36ZengMDPI AGSensors1424-82202021-08-012115524410.3390/s21155244The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine LearningRyszard K. Miler0Andrzej Kuriata1Anna Brzozowska2Akram Akoel3Antonina Kalinichenko4Faculty of Management and Finance, WSB University in Gdańsk, 80-266 Gdańsk, PolandFaculty of Management and Finance, WSB University in Gdańsk, 80-266 Gdańsk, PolandFaculty of Management, Czestochowa University of Technology, 42-201 Częstochowa, PolandThe Briese Schiffahrts GmbH & Co. KG, Hafenstraße 12, 26789 Leer, GermanyInstitute of Environmental Engineering and Biotechnology, University of Opole, 45-040 Opole, PolandMachine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for controlling algorithms. The aim of this paper is to present a game-based algorithm of controlling behaviours in the relation between an operator (OP) and a technical object (TO), based on the assumption that the game is logistics-oriented and the algorithm is to support ML applied in e-commerce optimization management. Algebraic methods, including matrices, Lagrange functions, systems of differential equations, and set-theoretic notation, have been used as the main tools. The outcome is a model of a game-based optimization process in a two-element logistics system and an algorithm applied to find optimal steering strategies. The algorithm has been initially verified with the use of simulation based on a Bayesian network (BN) and a structured set of possible strategies (OP/TO) calculated with the use of QGeNie Modeller, finally prepared for Python. It has been proved the algorithm at this stage has no deadlocks and unforeseen loops and is ready to be challenged with the original big set of learning data from a drone-operating company (as the next stage of the planned research).https://www.mdpi.com/1424-8220/21/15/5244e-commercemachine learning algorithmsa game-based systema logistics zero-sum gameBayesian network |
| spellingShingle | Ryszard K. Miler Andrzej Kuriata Anna Brzozowska Akram Akoel Antonina Kalinichenko The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning Sensors e-commerce machine learning algorithms a game-based system a logistics zero-sum game Bayesian network |
| title | The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning |
| title_full | The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning |
| title_fullStr | The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning |
| title_full_unstemmed | The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning |
| title_short | The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning |
| title_sort | algorithm of a game based system in the relation between an operator and a technical object in management of e commerce logistics processes with the use of machine learning |
| topic | e-commerce machine learning algorithms a game-based system a logistics zero-sum game Bayesian network |
| url | https://www.mdpi.com/1424-8220/21/15/5244 |
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